1. Field of the Invention
The invention relates to software and methods for fluid pipeline optimization and control, and more specifically, to optimization and control software and methods that can optimize for transient conditions within the fluid pipeline.
2. Description of Related Art
Fluid pipeline systems, such as gas transmission pipelines, operate at certain pressures and with certain flow rates in order to deliver fluid, for example, natural gas, to its destination. In the case of a gas pipeline, compressors along the pipeline maintain the pressures necessary to move the gas. In the case of a liquid pipeline, pumps move the liquid along the pipeline.
FIG. 1 is a diagram showing a typical gas pipeline system. Generally, referring to FIG. 1, a typical gas pipeline system may include multiple relay compressor stations with multiple points of supply and deliveries. For example, FIG. 1 shows a pipeline system having 6 compressor stations. Each individual station is controlled by control logic that, among other things, operates compressors and prevents a station from exceeding its maximum allowable operating pressures. The pipeline operator, through a supervisory control and data acquisition (SCADA) system, gives each individual compressor station's control logic its own target setpoints for suction pressure, discharge pressure and flow. The station's control logic seeks to maintain these target setpoints by starting and stopping compressors, as necessary. Additionally, as noted above, the control logic protects the station from exceeding its maximum allowable operating pressures and maintains it within safe operating parameters. However, the station control logic controls an individual station. Hence, it functions independent of the other stations in the system.
FIG. 2 is a diagram showing a pipeline flow control system that may be utilized to control the pipeline system of FIG. 1. Generally, referring to FIG. 2, a pipeline flow control system may include steady-state Optimization Software that calculates optimal target setpoints for the pipeline operator to manually send to the individual stations' control logic. Further, as FIG. 2 shows, the system may also include a multivariable control system (“Controller Software”) operating in conjunction with the optimization software. The multivariable controller software may include a set of controllers that attempts to drive a set of station discharge pressures to equal a set of discharge pressure targets calculated by the optimization software, and there may be one controller for each compressor station that is operating under multivariable control. Each controller attempts to manipulate the suction pressure of the compressor station it controls in order to drive the discharge pressure of the next upstream station toward its optimal discharge pressure target.
However, fluid pipelines are dynamic systems, and the control systems described with reference to FIG. 1 and FIG. 2 may not anticipate or take into account certain transient (i.e. non-steady state) conditions. Additionally, because each controller in the system of FIG. 2 typically controls its station in light of operating conditions at that station and the next upstream station only, the controller software is controlling individual stations on the pipeline, which are all interconnected, based on data gleaned from only a portion of the stations in the system. Hence, the controller software may not effectively control all stations on the pipeline system in light of transient conditions affecting the entire pipeline system or other portions of the pipeline system beyond the control of an individual controller. Accordingly, the controller software may, among other things, increase the cost of transporting fluid through the pipeline.
Further, the system shown in FIG. 2 utilizes a single set of tune parameters to handle all transient conditions but that are aimed at only controlling the setpoints of the immediate upstream compressor station. However, certain transient conditions may occur in the pipeline system that can not be efficiently or effectively managed by only controlling the setpoints of the immediate upstream compressor station. In such transient conditions, the controller software's single set of tune parameters does not provide the capability to adjust station operating parameters to effectively or timely handle the transient conditions. Hence, in this case, the stations' control logic over-rides the multivariable controller software and controls corresponding individual compressor station targets to near maximum operating pressures. Generally, this leads to an imbalance in the system, which usually results in not being able to take the full contracted supplies into the transmission system.
Additionally, the control system of FIG. 2 is not able to identify or transition to a new optimal solution when conditions change (e.g. supplies or deliveries of the transmission system) that require a change to the optimal compressor configuration. A particular problem encountered was when to start additional compressors when required for an optimal fuel-efficient system. Starting the additional compressors too early wastes fuel. On the other hand, starting the additional compressors too late may cause a transient condition that is beyond the capability of the controller software to control, resulting in station control logic overriding the controller software.